Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-13 03:26 UTC

pixelb / ps_mem

A utility to accurately report the in core memory usage for a program

PythonLGPL-2.1★ 1,636 stars⑂ 285 forkssince Sep 2013View on GitHub ↗
KindCommand-line toolLibraryhow this is determined

pixelb/ps_mem holds a health index of 19 out of 100, placing it in the Critical band. It scores highest on Community & Adoption (76/100) and lowest on Vitality (1/100). It was last updated 1394 days ago. A single contributor accounts for most of its recent work.

19
overall / 100
Critical

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

19
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 37 is calibrated to 31 on the published index scale (record calibration 2026-08-02).

Ownership

Pádraig BradyPersonal account
596 followers35 public repossince Jun 2010@facebook

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIps_mem3.141,433,13731537 days agomemoryramprofileprogramlinux

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

1Critical · 21% of overall
How it's scored
0/36Push recencylast push 1,394 days ago
0/36Commit cadence0/52 weeks with commits
0/18Commit volume0 commits in the last year
0/10OpenSSF Scorecard: Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year0
human_commit_share1
days_since_last_push1,394
active_weeks_last_year0
How it's scored
0/27Ships releasesno releases published
0/36Release recencyno releases
0/27Release cadenceno releases
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count0
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Signed-Releases. Remaining weights renormalized.

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

76Good · 17% of overall
How it's scored
52.1/60Stars1,636 stars
20.4/25Forks285 forks
10.3/15Watchers72 watchers
Inputs used
forks285
stars1,636
watchers72
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (LGPL-2.1)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateno
How it's scored
80/80Monthly downloads1,433,137 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesps_mem
dependents
ecosystemspypi
total_downloads
monthly_downloads1,433,137
unverified_packages_excluded
Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

50Moderate · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
6/22.5Commit distributiontop contributor authored 73% of commits
13.5/13.5Contributor breadth17 contributors
6/10OpenSSF Scorecard: Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
Inputs used
bus_factor1
contributors_sampled17
top_contributor_share0.732
How it's scored
28.3/42Issue resolution67% of issues closed
7.8/30PR acceptance7/27 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
3/15OpenSSF Scorecard: Code-ReviewFound 6/26 approved changesets -- score normalized to 2
Inputs used
merged_prs7
open_issues17
closed_issues35
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.673
closed_unmerged_prs20
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
10/30Ownership backingpersonal (user) account
0/20Verified domainnot applicable to user accounts
20/25Owner reach596 followers of pixelb
23.3/25Track record35 public repos, account ~16 yr old
Inputs used
followers596
owner_typeUser
is_verified
owner_loginpixelb
public_repos35
account_age_days5,889
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.
How it's scored
25/25Published & resolvable1 package(s) on pypi
4/35Publish recencylatest publish 1,537 days ago
12/20Version history3 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesps_mem
ecosystemspypi
any_deprecatedno
min_days_since_publish1,537

Engineering Quality

Are baseline engineering and documentation practices in place?

34At Risk · 19% of overall
How it's scored
0/24CI workflows
0/24Tests present
16/16Linter configtox.ini
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests0 out of 6 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_cino
has_testsno
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

60Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics5 topics
10/10Wiki
Inputs used
topicsram, memory, process, usage, shared
has_wikiyes
homepage
docs_site
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

29At Risk · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionbranch protection not enabled on development/release branches
0/2.5CI-Tests0 out of 6 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
1.5/7.5Code-ReviewFound 6/26 approved changesets -- score normalized to 2
1.5/2.5Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
0/10Dangerous-Workflowno data
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
0/7.5Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
0/5Packagingno data
0/5Pinned-Dependenciesno data
0/5SASTSAST tool is not run on all commits -- score normalized to 0
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsno data
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated13
scorecard_versionv5.5.0
checks_inconclusive5
scorecard_aggregate2.9
Excluded from scoring (no data or not applicable): Dangerous-Workflow, Packaging, Pinned-Dependencies, Signed-Releases, Token-Permissions. Remaining weights renormalized.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

26At Risk · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
30.9/40Legible commit history44 of 76 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.579
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
0/22Automated tests
11/11Lint / format configtox.ini
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practiceno agent-authored commits among the last 76
0/8Automated maintenanceno automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependenciesno data
Inputs used
has_nixno
has_testsno
lockfiles
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configyes
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Pinned-Dependencies. Remaining weights renormalized.
How it's scored
0/45Type-checkable codePython without a type-check config
55/55Manageable file sizes0/2 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes23,834
source_files_sampled2
oversized_source_files0

Key facts

1,636GitHub stars
17contributors
0commits, last 12 months
1,394days since last push
0releases
1bus factor
17open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

Star and fork history 0 ★ / 285 ⇿
0Stars
285Forks

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

05010015020025030028062013-092020-022026-07

Each point covers 12 days.

OpenSSF Scorecard 2.9 / 10
2.9aggregate

Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-08-13 03:25 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
0CI-Tests0 out of 6 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
2Code-ReviewFound 6/26 approved changesets -- score normalized to 2
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
n/aDangerous-Workflowno workflows found
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
n/aPackagingpackaging workflow not detected
n/aPinned-Dependenciesno dependencies found
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
n/aToken-PermissionsNo tokens found
10Vulnerabilities0 existing vulnerabilities detected
All dependencies 0

Full resolved dependency set from the GitHub dependency graph: 0 direct and 0 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
Dependency advisories not assessed

Advisory matching could not run for this report: No resolved dependencies to assess

Raw JSON report machine-readable

Feedback

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

The message is kept through sign-in.

Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.31.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.